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Record W1498093533

Settlement and Mediation in Canadian Legal Television

2011· article· en· W1498093533 on OpenAlexaffabout
Jennifer L. Schulz

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMediationSettlement (finance)Political scienceCharacter (mathematics)LawAlternative dispute resolutionTransformative mediationFace (sociological concept)SociologySocial psychologyPsychologySocial scienceBusiness
DOInot available

Abstract

fetched live from OpenAlex

This article is a close cultural legal analysis of The Associates, a Canadian legal television program. It describes what The Associates reveals about popular understandings of settlement and mediation in Canada. The show portrays negative attitudes toward settlement and mediation, such as 'settlement is second best' or 'caving in.' Uniquely, however, The Associates also portrays positive attitudes, such as 'mediation is the future of law.' The tension between these negative and positive attitudes is highlighted through the character of Robyn Parsons, the female associate who most often advocates for mediation on the show. Through the character of Robyn Parsons, the problems that women lawyers, women negotiators, and women mediation advocates face are examined. The article concludes by suggesting the possibility that television may be able to create a larger cultural legal space for mediation in society and greater positive exposure for mediators.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0240.014
Scholarly communication0.0090.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.254
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2011
Admission routes2
Has abstractyes

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